330-18 Spectral Response As a Tool for Assessing Plant Health Claims.

Poster Number 740

See more from this Division: C05 Turfgrass Science
See more from this Session: Turfgrass Ecology, Pest Management, and the Environment
Wednesday, October 19, 2011
Henry Gonzalez Convention Center, Hall C
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Dana G. Sullivan1, Richard T. Rees2, Yale Leiden1 and Mike Newnam3, (1)TurfScout, LLC, Greensboro, NC
(2)Bayer Crop Science AG, Research Triangle Park, NC
(3)Bayer Crop Science, Clayton, NC
Solar irradiance is the key ingredient of net primary production.  Characteristic patterns in spectral response properties of living vegetation, particularly in the visible and near-infrared, provide critical insights regarding changes in plant response to ambient environmental conditions.  Yet, until recently, obtaining such information was limited to satellite and airborne remote sensing systems; which were limited by expense, availability and ease of use.  With the advent of ground-based, commercially available sensors combined with web-based resources for data handling, turfgrass spectral response properties are being used as a means to assess plant health benefits associated with the application of certain pesticides.  The objective of the current study was to evaluate the power of rapid spectral data processing using TurfScout® (TurfScout® LLC, Tifton, GA) as a means to support plant health label claims as a component of pesticide management programs.  The study was conducted during 2011 at three locations:  1) Bayer Development and Training Center in Clayton, NC, 2) Wilson Country Club, Wilson, NC, and 3) Walnut Creek Country Club , Goldsboro, NC.  Data included radiometric measurements using ACS210 CropCircle (Holland Scientific, Lincoln, NE) along with visual ratings using a 1-9 scale.  Spectral data processing and analysis was conducted primarily with TurfScout®, which provides a web-based interface for near-instantaneous processing and display of the spectral data.  Assessments of sensitivity to plant response, accuracy and practicality using visual and spectral data will be made.
See more from this Division: C05 Turfgrass Science
See more from this Session: Turfgrass Ecology, Pest Management, and the Environment
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